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Fast Two-Step Blind Optical Aberration Correction

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Computer Vision – ECCV 2022 (ECCV 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13666))

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Abstract

The optics of any camera degrades the sharpness of photographs, which is a key visual quality criterion. This degradation is characterized by the point-spread function (PSF), which depends on the wavelengths of light and is variable across the imaging field. In this paper, we propose a two-step scheme to correct optical aberrations in a single raw or JPEG image,i.e., without any prior information on the camera or lens. First, we estimate local Gaussian blur kernels for overlapping patches and sharpen them with a non-blind deblurring technique. Based on the measurements of the PSFs of dozens of lenses, these blur kernels are modeled as RGB Gaussians defined by seven parameters. Second, we remove the remaining lateral chromatic aberrations (not contemplated in the first step) with a convolutional neural network, trained to minimize the red/green and blue/green residual images. Experiments on both synthetic and real images show that the combination of these two stages yields a fast state-of-the-art blind optical aberration compensation technique that competes with commercial non-blind algorithms.

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Acknowledgements

This work was partly financed by the DGA Astrid Maturation project “SURECAVI” no ANR-21-ASM3-0002, Office of Naval research grant N00014-17-1-2552. This work was performed using HPC resources from GENCI-IDRIS (grant 2022-AD011012453R1).

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Correspondence to Thomas Eboli .

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Eboli, T., Morel, JM., Facciolo, G. (2022). Fast Two-Step Blind Optical Aberration Correction. In: Avidan, S., Brostow, G., Cissé, M., Farinella, G.M., Hassner, T. (eds) Computer Vision – ECCV 2022. ECCV 2022. Lecture Notes in Computer Science, vol 13666. Springer, Cham. https://doi.org/10.1007/978-3-031-20068-7_40

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  • DOI: https://doi.org/10.1007/978-3-031-20068-7_40

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